* llvm-project: b5924a8e27536d19dd5c4d302db29fb6163d5faa
* mhlo: 848ca244d20f045b7921da55a98a04d95ef94f0e
* Multiple breakages that need to be fixed.
Fixes:
* Refactor dialect registration
* Remove all kindof methods (Casting functionality has been added upstream and is implicitly
available, see https://llvm.discourse.group/t/removing-kinds-from-attributes-and-types/1547.)
* Update dialect registration to comply with https://reviews.llvm.org/D85495.
* Remove type kinds and update some changed dialect signatures.
* Upgrade ATen dialect to match upstream needs.
* Move dialect registration to tablegen.
* Register the ListType in tablegen.
* Change dialect initialization signature.
* Use TypeSwitch in MlirIr location printer.
* Remove global registry depends from npcomp-opt.
* Change LowerToLLVM to pass an MLIRContext vs an LLVMDialect for type creation.
* Remove dep on MLIREDSCInterface that is removed upstream.
* Thread through the DialectRegistry for opt and python-like tools.
* Modernize pass registration (This was forced because the GEN_PASS_REGISTRATION code now generates inline functions vs literal pass registration statements)
Co-authored-by: Marius Brehler <marius.brehler@iml.fraunhofer.de>
* Rewrites public function signatures to operate on tensors (vs ndarray).
* Most of our backends presume immutable tensors at public function boundaries.
* This elides the very common code the compiler adds for chaining otherwise tensor-related numpy ops together.
* More aggressive canonicalizations would require more advanced analysis.
* Adds an op interface for adding CPA constraints.
* Adds a type conversion hook for handling built-in types (that we can't have adopt our interface).
* Converts tensor<> to object(!Tensor, [e:<type>]) just like NdArray.
* Implement a few numpy ops far enough to do dtype inference for simple sequences.
* Gets us passed the upstream changes that enable type interfaces.
* Adds the ARM backend due to an implicit IREE dependency sneaking in for that (https://github.com/google/iree/issues/2401)
* Adds explicit TypeStorage to type base classes per upstream change.
* This is intended to provide low-level modeling for built-in objects.
* It is now possible to trace slice tuples (which are tuples of NoneType|EllipsisType|SlotObjectType<slice, ...>).
* Creates an abstraction/registry around emitters (intended to generalize to AST compilation as well).
* Reworks ufuncs to use the same mechanism as array funcs.
* Adds the numpy.dot op.
Marius Brehler
Stella Laurenzo
Sean Silva